COURSE SUMMARY

The goals of the class are to introduce and develop skills in using the SAS statistical package, and to illustrate statistical concepts through the help of SAS. This class also intends to provide the bridge between Statistics 541 (Introduction to Biostatistics) and Population Health Sciences 800 (Quantitative Methods in Population Health I). In the class, we will cover

Data management and data manipulation using SAS.
SAS procedures for data analysis.
SAS graphical techniques for displaying data.
Use SAS to illustrate fundamental probability and statistical concepts, including random number generation, population, sample, probability distributions, random variables, hypothesis testing, p-value and confidence interval.

The course schedule will be closely related to Statistics 541. Therefore, students are expected to be well prepared about the course material of Statistics 541.

HANDOUTS AND RECOMMENDED TEXTS

Handouts corresponding to each lecture will be available on the course website before each class. While there are no required texts, it is good to have some SAS reference books. I find the following texts quite helpful:

“The Little SAS Book: A Primer, Second edition”, by Delwiche and Slaughter: a friendly easy-to-read guide introduces you to the most commonly used features of SAS software. Good for the SAS beginners.
“SAS Language and Procedures”, by SAS Institute Inc.: provide instructions and examples for using common features and procedures of SAS. Also good for the beginners.
“SAS/STAT User’s Guide”, by SAS Institute Inc.: references of all SAS statistics procedures. Good reference books for using SAS to do data analysis.
“SAS OnlineDoc” through the web link: http://shelf.doit.wisc.edu/SasOnLineDocs/onldoc.htm. To access this web page, you need to be in the University Ethernet or use the dialup through WiscWorld.

INTENDED AUDIENCE

The course will be of interest to master’s and Ph.D. students in population health sciences who are taking (or have taken) Statistics 541 and will also take Preventive Medicine 800.

METHOD OF STUDENT EVALUATION

The course grade will be based upon analyzing one of the provided data sets. Each student is required to hand in two homeworks based on the selected data set (25% for each) and write a ten-page or less (including all the texts, tables and graphics) scientific report of the analysis methods and results (50%). The detail format of the report will be given in class.

COURSE OUTLINE (may be subject to some modification during the semester)

Lecture 1 (9/3)	Introduction to SAS, including manipulating data in SAS, creating the temporary and permanent SAS data sets, and basic SAS programming.
Lecture 2 (9/10)	Introduction to SAS continued.
Lecture 3 (9/17)	Explore and graphically display data.
Lecture 4 (9/24)	SAS procedures for data exploration.
Lecture 5 (10/1)	Modify and combine SAS data sets.
Lecture 6 (10/8)	First homework due before the class. Random numbers and probability distributions in SAS.
Lecture 7 (10/15)	Advanced SAS programming.
Lecture 8 (10/22)	SAS macro.
Lecture 9 (10/29)	SAS procedures for hypothesis testing, including one-sample, two-sample and paired t-tests.
Lecture 10 (11/5)	Prevalence, incidence, relative risk, odds ratio and Kappa statistics.
Lecture 11 (11/12)	SAS procedures for analyzing categorical data, including Chi-square test, and tests for homogeneity and agreement.
Lecture 12 (11/19)	Second homework due before the class. SAS graph and output delivery system (ODS)
Lecture 13 (11/26)	SAS procedures for regression analysis.
Lecture 14 (12/3)	SAS procedures for nonparametric methods.
Lecture 15 (12/10)	Final project due before the class. Where to go from here.